Selecting Strategies and Managers
Choosing which strategies or managers to fund is a due-diligence problem as much as a quantitative one — track records matter, but process, risk controls, and how a strategy fits the rest of the book usually matter more.
Prerequisites: Allocating on Short, Noisy Track Records, Defining Sleeves in a Multi-Strategy Book
A multi-strategy firm evaluating a new pod, or an allocator evaluating an external manager, is rarely choosing between one obviously great option and one obviously bad one. Most candidates that make it to serious consideration have decent-looking track records, coherent stories, and reasonable references. The decision comes down to a narrower set of questions: does this strategy actually add something the book doesn't already have, is the process behind it repeatable, and are the risk controls strong enough that a bad month doesn't become a bad year.
Selecting strategies and managers is this evaluation process, and it weighs quantitative track record alongside qualitative due diligence in roughly equal measure, not track record alone.
A strong track record is necessary but not sufficient. The questions that separate a good addition to the book from a bad one are usually about process, risk discipline, and fit with existing sleeves — not about whose past Sharpe ratio is highest.
What actually gets evaluated
- Repeatability of process. Can the manager explain why the strategy works in a way that would still apply next year, or does the explanation only fit the specific trades that happened to work in the sample shown?
- Risk discipline. How does the manager behave during a drawdown — do they have a defined process for cutting risk, or does sizing decisions get made ad hoc under pressure?
- Fit with the existing book. A strategy with a mediocre standalone Sharpe ratio can still be a valuable addition if it's genuinely uncorrelated with everything else the firm runs; a strategy with an excellent standalone Sharpe ratio can be a poor addition if it's highly correlated with sleeves already in the book.
- Capacity and crowding. Is the strategy's edge large enough to survive the capital being proposed for it, or does it decay sharply once sized up?
Worked example
A firm evaluates two external managers for a new equity-market-neutral allocation. Manager X has a five-year track record with a 1.8 Sharpe ratio but is unwilling to disclose position-level detail or explain the strategy's logic beyond "proprietary machine learning." Manager Y has a three-year track record with a 1.1 Sharpe ratio, walks through the exact factor exposures and turnover of the strategy, and shows a clear, tested process for cutting gross exposure automatically when drawdown exceeds a set threshold. Despite the weaker headline number, the firm allocates to Manager Y — the strategy's logic is verifiable and independently plausible, its risk process is concrete, and its correlation to the firm's existing sleeves (estimated from disclosed factor exposures) is lower than Manager X's opaque strategy is assumed to have.
What this means in practice
Due diligence on a new strategy or manager should produce a written answer to "why will this keep working," not just a chart of past returns — a chart alone can't distinguish a repeatable process from a lucky run, and the earlier concepts on short track records and correlation estimation both explain exactly why the chart can't be trusted on its own.
Selecting managers primarily by ranking past Sharpe ratios is a well-known way to end up with a book of managers who all happened to get lucky in the same recent period — and because a shared recent tailwind is itself a form of correlation, the resulting book can end up far less diversified than a track-record-only ranking would suggest.
Further reading
- Ang, Asset Management: A Systematic Approach to Factor Investing (ch. 1)